ALICE: An open-source tool for automatic measurement of phoneme, syllable, and word counts from child-centered daylong recordings

Okko Räsänen*, Shreyas Seshadri, Marvin Lavechin, Alejandrina Cristia, Marisa Casillas

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu


Recordings captured by wearable microphones are a standard method for investigating young children’s language environments. A key measure to quantify from such data is the amount of speech present in children’s home environments. To this end, the LENA recorder and software—a popular system for measuring linguistic input—estimates the number of adult words that children may hear over the course of a recording. However, word count estimation is challenging to do in a language- independent manner; the relationship between observable acoustic patterns and language-specific lexical entities is far from uniform across human languages. In this paper, we ask whether some alternative linguistic units, namely phone(me)s or syllables, could be measured instead of, or in parallel with, words in order to achieve improved cross-linguistic applicability and comparability of an automated system for measuring child language input. We discuss the advantages and disadvantages of measuring different units from theoretical and technical points of view. We also investigate the practical applicability of measuring such units using a novel system called Automatic LInguistic unit Count Estimator (ALICE) together with audio from seven child-centered daylong audio corpora from diverse cultural and linguistic environments. We show that language-independent measurement of phoneme counts is somewhat more accurate than syllables or words, but all three are highly correlated with human annotations on the same data. We share an open-source implementation of ALICE for use by the language research community, enabling automatic phoneme, syllable, and word count estimation from child-centered audio recordings.

JulkaisuBehavior Research Methods
DOI - pysyväislinkit
TilaHyväksytty/In press - 1 tammikuuta 2020
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

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  • Projektit

    • 2 Päättynyt

    Ihmisen ja koneen kielenoppimisen kontekstisidonnainen laskennallinen perusta

    Räsänen, O.


    Projekti: Academy of Finland: Other research funding

    ACLEW: Lasten kielikokemuksien kartoitus ja analyysi koko maailman mittakaavassa

    Räsänen, O. & Seshadri, S.


    Projekti: Academy of Finland: Other research funding

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